{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,20]],"date-time":"2026-02-20T00:26:48Z","timestamp":1771547208906,"version":"3.50.1"},"reference-count":37,"publisher":"MDPI AG","issue":"10","license":[{"start":{"date-parts":[[2022,10,13]],"date-time":"2022-10-13T00:00:00Z","timestamp":1665619200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"National Natural Science Foundation of China","award":["61862061"],"award-info":[{"award-number":["61862061"]}]},{"name":"National Natural Science Foundation of China","award":["61563052"],"award-info":[{"award-number":["61563052"]}]},{"name":"National Natural Science Foundation of China","award":["61163028"],"award-info":[{"award-number":["61163028"]}]},{"name":"National Natural Science Foundation of China","award":["2021D01C119"],"award-info":[{"award-number":["2021D01C119"]}]},{"name":"Science and Technology Plan Project of Xinjiang Uyghur Autonomous Region, China","award":["61862061"],"award-info":[{"award-number":["61862061"]}]},{"name":"Science and Technology Plan Project of Xinjiang Uyghur Autonomous Region, China","award":["61563052"],"award-info":[{"award-number":["61563052"]}]},{"name":"Science and Technology Plan Project of Xinjiang Uyghur Autonomous Region, China","award":["61163028"],"award-info":[{"award-number":["61163028"]}]},{"name":"Science and Technology Plan Project of Xinjiang Uyghur Autonomous Region, China","award":["2021D01C119"],"award-info":[{"award-number":["2021D01C119"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Information"],"abstract":"<jats:p>Handwritten signatures have traditionally been used as a common form of recognition and authentication in tasks such as financial transactions and document authentication. However, there are few studies on minority languages such as Uyghur and Kazakh used in Xinjiang, China, and no available public dataset for these scripts, which are widely used in banking and other fields. Therefore, this paper addresses this problem by constructing a dataset containing Uyghur, Kazakh, and Han languages and presents an automatic handwritten signature recognition approach based on Uyghur, Kazakh, Han, and public datasets. In the paper, a handwritten signature recognition method that combines local maximum occurrence features (LOMO) and histogram of orientated gradients (HOG) features was proposed. LOMO features use a sliding window to represent the local features of the signature image. The high-dimensional features formed by the combination of these methods are dimensionally reduced by principal component analysis (PCA). The classification is performed using k-nearest neighbors (k-NN), and it is compared with the random forest method. The proposed method achieved a recognition rate of 98.4% using a diverse signature database compared with existing methods. It shows that the method was effective and can be applied to large datasets of mixed, multilingual signatures.<\/jats:p>","DOI":"10.3390\/info13100496","type":"journal-article","created":{"date-parts":[[2022,10,13]],"date-time":"2022-10-13T22:21:11Z","timestamp":1665699671000},"page":"496","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":10,"title":["Multilingual Handwritten Signature Recognition Based on High-Dimensional Feature Fusion"],"prefix":"10.3390","volume":"13","author":[{"given":"Aliya","family":"Rexit","sequence":"first","affiliation":[{"name":"School of Information Science and Engineering, Xinjiang University, Urumqi 830046, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Mahpirat","family":"Muhammat","sequence":"additional","affiliation":[{"name":"Institue of International Culture and Exchange, Xinjiang University, Urumqi 830046, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xuebin","family":"Xu","sequence":"additional","affiliation":[{"name":"School of Information Science and Engineering, Xinjiang University, Urumqi 830046, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Wenxiong","family":"Kang","sequence":"additional","affiliation":[{"name":"School of Automation Science and Engineering, South China University of Technology, Guangzhou 510641, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5464-0594","authenticated-orcid":false,"given":"Alimjan","family":"Aysa","sequence":"additional","affiliation":[{"name":"Key Laboratory of Xinjiang Multilingual Information Processing, Urumqi 830046, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7566-6494","authenticated-orcid":false,"given":"Kurban","family":"Ubul","sequence":"additional","affiliation":[{"name":"School of Information Science and Engineering, Xinjiang University, Urumqi 830046, China"},{"name":"Key Laboratory of Xinjiang Multilingual Information Processing, Urumqi 830046, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2022,10,13]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Engin, D., Kantarci, A., Arslan, S., and Ekenel, H.K. 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